Thumbnail Extraction for Multipoint Geostatistical Subsoil Modeling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional geostatistical methods are limited in representing complex geological structures and heterogeneities, particularly in accurately modeling subsoil areas for oil field exploration, due to their inability to effectively incorporate dynamic connectivity information between wells.
Innovation Solution
A method is proposed that constructs a training image on a three-dimensional grid, incorporating well data and inter-well connectivity information to improve the representativeness of multipoint geostatistical simulations by selecting and verifying thumbnails based on facies and connectivity patterns, ensuring the model satisfies observed hydrodynamic conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional geostatistical methods are used to model subsoil areas, then the modeling process is simple and fast, but the ability to represent complex geological structures and heterogeneities is limited
Solution Approach 1:
The patent segments the geological model into training images and thumbnails. The training image is divided into multiple thumbnails that are extracted and used to constrain the multipoint geostatistical modeling. This segmentation allows complex geological structures to be represented through multiple simplified patterns while maintaining overall model accuracy.
Solution Approach 2:
The patent transitions from traditional two-point statistics to multipoint statistics by extracting three-dimensional thumbnails from training images. This dimensional approach enables the model to capture spatial heterogeneities and complex topologies that traditional methods cannot represent, significantly improving geological structure representation.
2Reliability
If multipoint geostatistical methods are used to improve representation of geological heterogeneities, then the model accuracy improves, but the computational complexity and data processing requirements increase
Solution Approach 1:
The patent performs preliminary extraction of thumbnails from training images before the actual geostatistical modeling. By pre-processing the training image to extract and store multiple thumbnails representing different geological patterns, the subsequent multipoint modeling process is simplified and more efficient, reducing computational complexity while maintaining high representativeness.
Solution Approach 2:
The patent creates multiple copies of the training image in the form of thumbnails that capture different spatial patterns. These thumbnails serve as constrained patterns for the multipoint simulation, allowing the model to reproduce complex geological heterogeneities without requiring the entire training image to be processed, thus reducing computational burden.
3Reliability
If training images are used to represent geological patterns, then the model can capture spatial heterogeneities, but the ability to incorporate dynamic connectivity information between wells is limited
Solution Approach 1:
The patent incorporates dynamic connectivity information between wells by extracting thumbnails that capture spatial patterns and using them to constrain multipoint geostatistical modeling. This dynamic approach allows the model to adapt to observed hydrodynamic conditions and inter-well connectivity data, enabling the representation of time-dependent or observation-dependent geological characteristics.
Solution Approach 2:
The patent uses observed well data and inter-well connectivity information as feedback to constrain the multipoint simulation. By extracting thumbnails from training images and using them to guide the modeling process, the system incorporates observed geological and hydrodynamic conditions, allowing the model to adjust and refine its representation of connectivity based on actual measurements.
Data Source
AI summary
According to the invention, in order to initialize the use of a multipoint geostatistical technique (MPS), the method takes information, which was collected in wells drilled in the area of the subsoil to be modeled, into account. Particularly, the method takes inter-well connectivity data into account, which indicate one or more groups of cells of a reservoir grid that are located along a plurality of wells and between which hydrodynamic communications have been observed. For each of said groups, compatible thumbnail images are searched for in a training image used in the MPS technique. Said thumbnail images have, in the training image, facies that enable the flows between the cells of the group. The thumbnail images are applied onto the reservoir grid in order to initialize MPS simulation while ensuring that the inter-well connectivity constraints will be respected.